/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "blenders.hpp" #include "util.hpp" using namespace std; using namespace cv; static const float WEIGHT_EPS = 1e-5f; Ptr Blender::createDefault(int type) { if (type == NO) return new Blender(); if (type == FEATHER) return new FeatherBlender(); if (type == MULTI_BAND) return new MultiBandBlender(); CV_Error(CV_StsBadArg, "unsupported blending method"); return NULL; } void Blender::prepare(const vector &corners, const vector &sizes) { prepare(resultRoi(corners, sizes)); } void Blender::prepare(Rect dst_roi) { dst_.create(dst_roi.size(), CV_16SC3); dst_.setTo(Scalar::all(0)); dst_mask_.create(dst_roi.size(), CV_8U); dst_mask_.setTo(Scalar::all(0)); dst_roi_ = dst_roi; } void Blender::feed(const Mat &img, const Mat &mask, Point tl) { CV_Assert(img.type() == CV_16SC3); CV_Assert(mask.type() == CV_8U); int dx = tl.x - dst_roi_.x; int dy = tl.y - dst_roi_.y; for (int y = 0; y < img.rows; ++y) { const Point3_ *src_row = img.ptr >(y); Point3_ *dst_row = dst_.ptr >(dy + y); const uchar *mask_row = mask.ptr(y); uchar *dst_mask_row = dst_mask_.ptr(dy + y); for (int x = 0; x < img.cols; ++x) { if (mask_row[x]) dst_row[dx + x] = src_row[x]; dst_mask_row[dx + x] |= mask_row[x]; } } } void Blender::blend(Mat &dst, Mat &dst_mask) { dst_.setTo(Scalar::all(0), dst_mask_ == 0); dst = dst_; dst_mask = dst_mask_; dst_.release(); dst_mask_.release(); } void FeatherBlender::prepare(Rect dst_roi) { Blender::prepare(dst_roi); dst_weight_map_.create(dst_roi.size(), CV_32F); dst_weight_map_.setTo(0); } void FeatherBlender::feed(const Mat &img, const Mat &mask, Point tl) { CV_Assert(img.type() == CV_16SC3); CV_Assert(mask.type() == CV_8U); int dx = tl.x - dst_roi_.x; int dy = tl.y - dst_roi_.y; createWeightMap(mask, sharpness_, weight_map_); for (int y = 0; y < img.rows; ++y) { const Point3_* src_row = img.ptr >(y); Point3_* dst_row = dst_.ptr >(dy + y); const float* weight_row = weight_map_.ptr(y); float* dst_weight_row = dst_weight_map_.ptr(dy + y); for (int x = 0; x < img.cols; ++x) { dst_row[dx + x].x += static_cast(src_row[x].x * weight_row[x]); dst_row[dx + x].y += static_cast(src_row[x].y * weight_row[x]); dst_row[dx + x].z += static_cast(src_row[x].z * weight_row[x]); dst_weight_row[dx + x] += weight_row[x]; } } } void FeatherBlender::blend(Mat &dst, Mat &dst_mask) { normalize(dst_weight_map_, dst_); dst_mask_ = dst_weight_map_ > WEIGHT_EPS; Blender::blend(dst, dst_mask); } void MultiBandBlender::prepare(Rect dst_roi) { Blender::prepare(dst_roi); dst_pyr_laplace_.resize(num_bands_ + 1); dst_pyr_laplace_[0] = dst_; dst_band_weights_.resize(num_bands_ + 1); dst_band_weights_[0].create(dst_roi.size(), CV_32F); dst_band_weights_[0].setTo(0); for (int i = 1; i <= num_bands_; ++i) { dst_pyr_laplace_[i].create((dst_pyr_laplace_[i - 1].rows + 1) / 2, (dst_pyr_laplace_[i - 1].cols + 1) / 2, CV_16SC3); dst_band_weights_[i].create((dst_band_weights_[i - 1].rows + 1) / 2, (dst_band_weights_[i - 1].cols + 1) / 2, CV_32F); dst_pyr_laplace_[i].setTo(Scalar::all(0)); dst_band_weights_[i].setTo(0); } } void MultiBandBlender::feed(const Mat &img, const Mat &mask, Point tl) { CV_Assert(img.type() == CV_16SC3); CV_Assert(mask.type() == CV_8U); Point tl_new(dst_roi_.tl()); Point br_new(dst_roi_.br()); int top = tl.y - tl_new.y; int left = tl.x - tl_new.x; int bottom = br_new.y - tl.y - img.rows; int right = br_new.x - tl.x - img.cols; // Create the source image Laplacian pyramid vector src_pyr_gauss(num_bands_ + 1); src_pyr_gauss[0] = img; copyMakeBorder(img, src_pyr_gauss[0], top, bottom, left, right, BORDER_REFLECT); for (int i = 0; i < num_bands_; ++i) pyrDown(src_pyr_gauss[i], src_pyr_gauss[i + 1]); vector src_pyr_laplace; createLaplacePyr(src_pyr_gauss, src_pyr_laplace); src_pyr_gauss.clear(); // Create the weight map Gaussian pyramid Mat weight_map; mask.convertTo(weight_map, CV_32F, 1./255.); vector weight_pyr_gauss(num_bands_ + 1); copyMakeBorder(weight_map, weight_pyr_gauss[0], top, bottom, left, right, BORDER_CONSTANT); for (int i = 0; i < num_bands_; ++i) pyrDown(weight_pyr_gauss[i], weight_pyr_gauss[i + 1]); // Add weighted layer of the source image to the final Laplacian pyramid layer for (int i = 0; i <= num_bands_; ++i) { int dx = 0;//(tl_new.x >> i) - (dst_roi_.x >> i); int dy = 0;//(tl_new.y >> i) - (dst_roi_.y >> i); for (int y = 0; y < src_pyr_laplace[i].rows; ++y) { const Point3_* src_row = src_pyr_laplace[i].ptr >(y); Point3_* dst_row = dst_pyr_laplace_[i].ptr >(y + dy); const float* weight_row = weight_pyr_gauss[i].ptr(y); float* dst_weight_row = dst_band_weights_[i].ptr(y + dy); for (int x = 0; x < src_pyr_laplace[i].cols; ++x) { dst_row[x + dx].x += static_cast(src_row[x].x * weight_row[x]); dst_row[x + dx].y += static_cast(src_row[x].y * weight_row[x]); dst_row[x + dx].z += static_cast(src_row[x].z * weight_row[x]); dst_weight_row[x + dx] += weight_row[x]; } } } } void MultiBandBlender::blend(Mat &dst, Mat &dst_mask) { for (int i = 0; i <= num_bands_; ++i) normalize(dst_band_weights_[i], dst_pyr_laplace_[i]); restoreImageFromLaplacePyr(dst_pyr_laplace_); dst_ = dst_pyr_laplace_[0]; dst_mask_ = dst_band_weights_[0] > WEIGHT_EPS; dst_pyr_laplace_.clear(); dst_band_weights_.clear(); Blender::blend(dst, dst_mask); } ////////////////////////////////////////////////////////////////////////////// // Auxiliary functions Rect resultRoi(const vector &corners, const vector &sizes) { Point tl(numeric_limits::max(), numeric_limits::max()); Point br(numeric_limits::min(), numeric_limits::min()); CV_Assert(sizes.size() == corners.size()); for (size_t i = 0; i < corners.size(); ++i) { tl.x = min(tl.x, corners[i].x); tl.y = min(tl.y, corners[i].y); br.x = max(br.x, corners[i].x + sizes[i].width); br.y = max(br.y, corners[i].y + sizes[i].height); } return Rect(tl, br); } void normalize(const Mat& weight, Mat& src) { CV_Assert(weight.type() == CV_32F); CV_Assert(src.type() == CV_16SC3); for (int y = 0; y < src.rows; ++y) { Point3_ *row = src.ptr >(y); const float *weight_row = weight.ptr(y); for (int x = 0; x < src.cols; ++x) { row[x].x = static_cast(row[x].x / (weight_row[x] + WEIGHT_EPS)); row[x].y = static_cast(row[x].y / (weight_row[x] + WEIGHT_EPS)); row[x].z = static_cast(row[x].z / (weight_row[x] + WEIGHT_EPS)); } } } void createWeightMap(const Mat &mask, float sharpness, Mat &weight) { CV_Assert(mask.type() == CV_8U); distanceTransform(mask, weight, CV_DIST_L1, 3); threshold(weight * sharpness, weight, 1.f, 1.f, THRESH_TRUNC); } void createLaplacePyr(const vector &pyr_gauss, vector &pyr_laplace) { if (pyr_gauss.size() == 0) return; pyr_laplace.resize(pyr_gauss.size()); Mat tmp; for (size_t i = 0; i < pyr_laplace.size() - 1; ++i) { pyrUp(pyr_gauss[i + 1], tmp, pyr_gauss[i].size()); subtract(pyr_gauss[i], tmp, pyr_laplace[i]); } pyr_laplace[pyr_laplace.size() - 1] = pyr_gauss[pyr_laplace.size() - 1].clone(); } void restoreImageFromLaplacePyr(vector &pyr) { if (pyr.size() == 0) return; Mat tmp; for (size_t i = pyr.size() - 1; i > 0; --i) { pyrUp(pyr[i], tmp, pyr[i - 1].size()); add(tmp, pyr[i - 1], pyr[i - 1]); } }